Candida albicans versus Mycobacterium tuberculosis: infection-specific human immune responses

Introduction

Systemic infection of the human host can arise from several pathogenic bacteria as well as from fungal species, and it is of high clinical relevance to trace back the nature of infection from the host response. Amongst these systemic infections are sepsis inducers Candida albicans and Mycobacterium tuberculosis, responsible for a great amount of worldwide deaths [1]. Sepsis, however, does not necessarily originate from infection. Traumas and non-infection-based injuries can also trigger an unbound inflammatory response from the human host most commonly known as systemic inflammatory response syndrome. Both cases, infection and non-infection, nevertheless display similar clinical symptoms with significantly better recovery times of patients included in the latter. Despite the clinical similarities, studies have suggested that distinct infection-induced host responses from different pathogens occur, namely at the signalling pathway level [2].

Methods

Studies have been performed focused on common gene expression profiles between several pathogens [3]. However, understanding the difference in immune responses between these two pathogens, but not exclusively, might lead to better diagnostic tools and treatment decision-making. Relying on systems biology concepts and bioinformatics tools, we use gene expression data to distinguish C. albicans and M. tuberculosis infections in the human host; for example, cellular regulation and communication between host immune cells and pathogens [4, 5].

Results

We have, in a first analysis, focused on the cytokine-cytokine signalling pathway due to its role in inflammation response towards infections. Genes belonging to the IL-2 cytokine family are only expressed when facing infection by C. albicans in comparison to M. tuberculosis suggesting a tendency towards B-cell proliferation and production of antibodies. However, during infection caused by M. tuberculosis, no significant changes in gene expression occur in this pathway that indicates a specific immune response for this pathogen. Further analysis of additional signalling pathways might highlight other human infection-specific immune responses in regards to the pathogens considered.

Conclusion

Next we will focus on developing a mathematical model capable of simulating such immune responses and possibly identifying genes and pathways which might clarify how these inflammation responses can be targeted, countered and moderated [6].